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MicrosoftSQL Server 2016 (CTP3) contains a preview version of R Services (In-database). This new product includes provides closer integration of R with enterprise data sources such as SQL Server databases.
In This Topic
Get the CTP3 Samples
Link to downloadable data and sample scripts
Developing an End-to-End Data Science Solution
Learn how to build a solution, deploy it to SQL Server, and perform scoring
SQL Server R Services for the Data Scientist
Learn more about the enhanced packages provided by Microsoft R Open 3.2.2 and how to use them with SQL Server data
Get the CTP3 Samples
Product samples for SQL Server 2016 are available from the Microsoft Download Center:
SQL Server 2016 Product Samples
This download includes the AdventureWorks databases, as well as samples for new features such as Stretch Database.
Tip
To get only the samples for R Services (In-database), select the zip file, and open the folder Advanced Analytics.
Developing an End-to-End Data Science Solution
Data Science End-to-End Walkthrough
This solution uses the New York City Taxi data set to demonstrate the entire data science process:
Import data to SQL Server
Build a predictive model using R
Deploy the R model to SQL Server
Use the model in production for scoring
Start here if you want to learn how to use the new functions provided by the RevoScaleR package to work with SQL Server data in R.
Note
For additional examples of how the New York City taxi dataset is used in machine learning, see Building Azure ML Models on the NYC Taxi Dataset.
SQL Server R Services for the Data Scientist
The following walkthrough, currently available in PDF format from the Microsoft Download Center, assumes that you are already familiar with the R language and want to learn how to use the new database integration features, such as the ability to change execution context.
Getting Started with RevoScaleR and SQL Server
The walkthrough explains the functionality of the new R packages and functions provided by Revolution R Enterprise 7.5.0, including:
Defining a SQL Server data source
Uploading data from a CSV file into a SQL Server database by using R
Using R to modify tables and add column metadata
Using the enhanced RevoScale R packages in SQL Server
Creating predictive models and storing them in SQL Server
Using stored models to generate predictions
Depending on your familiarity with R, the walkthrough should take between 60 and 90 minutes to complete.
Additional Samples and Blogs
This blog post outlines the process of using the R packages and functions provided by R Services (In-database) to connect to SQL Server. Sample code is provided.
Note
If you need more information about learning the R language, or want to learn more about the R packages provided in R Services (In-database), see these resources.
See Also
Getting Started with SQL Server R Services
SQL Server R Services Features and Tasks